Generate llms.txt and llms-full.txt indexes from markdown directories or URLs.
npx skills add https://github.com/Thanh-apero/apero-kit-cli --skill ck-llms-thanh-apero
Please help me install this Agent Skill. Skill: ck:llms Source: https://github.com/Thanh-apero/apero-kit-cli/tree/main/.claude/skills/llms Command: npx skills add https://github.com/Thanh-apero/apero-kit-cli --skill ck-llms-thanh-apero
This Skill solves the problem of generating LLM-friendly documentation indexes, making it easier for AI systems to access and understand the project's documentation.
llms.txt and llms-full.txt files with curated content and inline full document content.Run the skill with python3 scripts/generate-llms-txt.py --source ./docs --base-url https://example.com/docs.
High-intent search queries and answers about installing and using this skill.
To generate an llms.txt file, run the provided Python script against your markdown directory using the command line interface. You can specify the source path and an optional base URL to create a structured, LLM-friendly documentation index.
An llms.txt file provides a curated index of your documentation, whereas an llms-full.txt file includes the inline full document content. You can use a command flag to toggle generating the full content version during the indexing process.
Yes, you can set a custom output location and a base URL for links when generating your LLM-friendly site indexing files. This allows you to accurately map directory structures to live web URLs during the documentation scanning process.
Yes, you need a Python environment to execute the script that creates AI-friendly documentation indexes. The skill relies on Python to automatically scan your markdown files and output the structured llms.txt files.
The best way to make project documentation discoverable by AI systems is to generate an llms.txt file. This creates a structured, LLM-friendly index that AI systems can easily access and understand from your markdown files.
This documentation indexing tool works with both local directories and remote URLs. When scanning from a URL, you can set a base URL parameter to ensure the generated llms.txt file contains correct absolute links.
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